Sector Selection for Granular Employment in Same Company

Running an analysis of new expected employment at an expanding company. Now, I have all the positions titles, salaries, and start dates. What I’m having issues with are assigning sectors to the new roles.

Example: a Field Installation Technician. Now, a pretty straightforward job installing modems/routers, etc for an internet company. What I can’t find is an appropriate home for them under sector. Even searching their NAICS in the sector search comes up with no results.

I know that there are options under sector for something like “Wired Telecommunications Provider” or such, but I assumed that since I have the granular data it would help the analysis if I could run the separate employee categories on their own (as a Customer Service Rep won’t make or spend the same as certain managers).

Unless I should plug them all into the Wired Telecom sector and just adjust the “Employee Compensation” variable? But then it gives me a warning about making it a custom event.

Comments

I see that you have the position titles, salaries and start dates and want to model how the expanded employment will ripple through the economy. The first question here I would have for you is whether you have additional data or if it’s only the titles, salaries and start dates? If so, that’s entirely fine but if you had other information as well, it may change the below answers to some of your questions.

If you’re searching by a specific NAICS that you aren’t finding, it’s possible that the code was changed after 2012 and you may want to search by the name or keywords (IMPLAN uses the codes prior to 2012 to correlate with our sectors). In the case of Wired Telecommunications Carriers, the code was changed from 517110 to 517311 so if you try the earlier code, it’ll work. This matches with IMPLAN sector 427 which includes numerous telecommunications categories. HERE is the link for the sector bridge that should assist in the future (NAICS (2012) TO IMPLAN 536 BRIDGE)

While you have options on how to proceed, you could certainly be on the right track by thinking to run this as an industry change and with your mindset as to how you should continue. As you stated, likely the best method would be to use sector 427 (i.e. field technician, customer service rep, etc) and adjust the inputs accordingly on the event. Because your employees all fall into the sector “Wired Telecommunications Provider”, you’d be able to capture the variance in their income by using their compensation as your starting value and then customizing the employment count (which generates the custom event “warning”… this warning is just to make you aware the you are deviating for IMPLAN’s industry average ratios). If you had Sales Revenue or Output, you’d want to start with that in Industry Sales, then customize from there. Since IMPLAN uses aggregate data, providing the employee compensation and the employment count for all the new people will split that money between the group using the ratios IMPLAN typically uses for that region/sector.

You should be aware that the order of your inputs is important here. You should begin by choosing the sector and then the year (event options > edit event properties > event year) if you are using IMPLAN Pro and choosing the year that represents the first year in which the new employees would be paid that amount. After this, you should be entering employee compensation (total compensation amount of all the new hires), and then employment. Any numbers you don’t have should not be input and the system will calculate them. This is summed up below:

Sector

Event Year (year of the dollar in your analysis/ year employees are paid)

If you have it – Industry Sales

If you have it – Employee Compensation (customize Proprietor Income if necessary)

If you have it – Employment

The numbers calculated from this event will follow the spending pattern that is average for that industry… so it may not be necessary to do anything more complicated if the new hires you’re studying resemble a normal distribution for this region.

This approach will not reflect the variance in how these employees spend their money (difference in spending pattern if they make 15-30K vs 70-100k). Instead, the compensation of the workers will be divided and modeled in spending patterns that parallel the breakdown of income groups in that region. With your granular data, you can make your analysis some degree more accurate (but a bit more work-intensive) by performing an Analysis-by-Parts. How much this changes your results will depend on how different the breakdown of income groups in the region is compared to the business/industry you are analyzing. I tested the variance in results of the two methods using Sector 427 in a random region, and found only a 2% variance…. So it may not be worth your time doing this extra work.

You can read more about Analysis by Parts HERE. To use this method and account for the variance in income groups of employees (and in turn, variance in spending patterns), you’d need to use a “Household Income Change” Activity for Part 3 instead of a Labor Income Change. For a Household Income Change, you’d need to know the total amount of new income for the region and income group (income should exclude all payroll tax and employees that live outside of the region).

I am going to first choose Sector, and for all positions (whether they're field techs, accountant, or administrators) choose the same sector, in this case 427. I should create a new Event for each position because I will be changing Employee Compensation, and then Employment, in that order. The variance in spending patterns which I was concerned about (due to the varied positions) will be handled through modeling based on the income group in the region.

I think this answered my main question that I didn't know how to ask, which was if spending patterns were based on the Sector of employment or the Income level (although I'm sure it's a bit of both for more accuracy).

Does this sound correct so far? I may attempt an Analysis-by-Parts, but would need to learn the theory and execution before I'm back here for advice.

I apologize if my previous response was confusing and want to elaborate on what you've asked above.

First, there are essentially two ways for you to do this depending on what you're looking for (assuming you've decided not to attempt ABP):

1) You can do a single activity with a single event and just use the total employee compensation, the total number of employees being hired, and any other information you have.

2) The other option is just to create an activity for each job position (i.e. field technician, manager, etc) with 1 event and 1 activity. Then you can use the sum of employee compensation for that specific job and the number of people taking that position. This would allow you to compare how each job individually will impact the economy.

In both cases, you would be using the same sector (427) since this sector should include the various positions you have. Remember, the sector is industry-specific (not job specific) so it would be incorrect to think a manager would fall in to a different sector.

The spending patterns will be handled by modeling based on income groups and the spending patterns are based on those income groups, not sector of employment and region. Sorry if I miscommunicated that concept. When you don't use the spending patterns - the employee compensation will be run through the different income group categories in portion to the breakdown of those income groups in that region (which is what you would be doing).

This link will also provide a case study for ABP if you're interested in reading over that.